Worker well-being is a hot topic in organizations, consultancy and academia. However, too often, the buzz about worker well-being, enthusiasm for new programs to promote it and interest to research it, have not been accompanied by universal enthusiasm for scientific measurement. Aim to bridge this gap, we address three questions. To address the question ‘What is worker well-being?’, we explain that worker well-being is a multi-facetted concept and that it can be operationalized in a variety of constructs. We propose a four-dimensional taxonomy of worker well-being constructs to illustrate the concept’s complexity and classify ten constructs within this taxonomy. To answer the question ‘How can worker well-being constructs be measured?’, we present two aspects of measures: measure obtrusiveness (i.e., the extent to which obtaining a measure interferes with workers’ experiences) and measure type (i.e., closed question survey, word, behavioral and physiological). We illustrate the diversity of measures across our taxonomy and uncover some hitherto under-appreciated avenues for measuring worker well-being. Finally, we address the question ‘How should a worker well-being measure be selected?’ by discussing conceptual, methodological, practical and ethical considerations when selecting a measure. We summarize these considerations in a short checklist. It is our hope that with this study researchers – working in organizations, in academia or both – will feel more competent to find effective strategies for the measurement worker well-being and eventually make policies and choices with a better understanding of what drives worker well-being.

The Standard Assumption about Well-Being and the Goodness of a Life Some assessments of what is good for a person focus on the state of the person at a moment or during a short period of time and how the person is faring then. These are assessments of the person's well-being at that time. Other assessments take the person's full life into view, saying how good that life is on the whole. These are assessments of life-goodness. Thus delineated, assessments of well-being and assessments life-goodness are different. That cannot be a controversial point. After all, the respective objects of assessment-the state of a person at a time and the series of events that compose a life-are of different kinds. But also uncontroversial is the assumption that these two kinds of assessment are so closely related that one can be understood in terms of the other via the principle that well-being makes a life good for the person who lives it. 1 I will argue that, even on a weak interpretation of this principle, it is not true. Refuting that weak con-1. Assumptions along these lines are so pervasive that philosophers considering well-being and life-goodness do not usually treat the two notions separately. Derek Parfit's Appendix I to Reasons and Persons, which has been, since its publication, the standard starting point for discussions of well-being, introduces his topic by asking, "What would be best for someone, or would be most in this person's interests, or would make this person's life go, for him, as well as possible?" (1984: 493). At the beginning of Welfare, Happiness, and Ethics, Wayne Sumner states that welfare "attaches pre-eminently to the lives of individuals," and he goes on to say "a person's welfare is more or less the same as her well-being or interest" (1996: 1). In the introduction to Pleasure and the Good Life, Fred Feldman identifies "the Good Life" as "a life that is good in itself for the one who lives it," and he notes, "Some philosophers speak here of 'personal welfare' or 'well-being'. A good life, in this sense, would be a life that is outstanding in terms of welfare, or well-being" (2004: 9). Additional examples abound.

A self-fulfilling prophecy (SFP) in neuroprognostication occurs when a patient in coma is predicted to have a poor outcome, and life-sustaining treatment is withdrawn on the basis of that prediction, thus directly bringing about a poor outcome (viz. death) for that patient. In contrast to the predominant emphasis in the bioethics literature, we look beyond the moral issues raised by the possibility that an erroneous prediction might lead to the death of a patient who otherwise would have lived. Instead, we focus on the problematic epistemic consequences of neuroprognostic SFPs in settings where research and practice intersect. When this sort of SFP occurs, the problem is that physicians and researchers are never in a position to notice whether their original prognosis was correct or incorrect, since the patient dies anyway. Thus, SFPs keep us from discerning false positives from true positives, inhibiting proper assessment of novel prognostic tests. This epistemic problem of SFPs thus impedes learning, but ethical obligations of patient care make it difficult to avoid SFPs. We then show how the impediment to catching false positive indicators of poor outcome distorts research on novel techniques for neuroprognostication, allowing biases to persist in prognostic tests. We finally highlight a particular risk that a precautionary bias towards early withdrawal of life-sustaining treatment may be amplified. We conclude with guidelines about how researchers can mitigate the epistemic problems of SFPs, to achieve more responsible innovation of neuroprognostication for patients in coma.

This article addresses three questions about well-being. First, is wellbeing future-sensitive? I.e., can present well-being depend on future events? Second, is well-being recursively dependent? I.e., can present well-being (non-trivially) depend on itself? Third, can present and future well-being be interdependent? The third question combines the first two, in the sense that a yes to it is equivalent (given some natural assumptions) to yeses to both the first and second. To do justice to the diverse ways we contemplate well-being, I consider our thought and discourse about well-being in three domains: everyday conversation, social science, and philosophy. This article's main conclusion is that we must answer the third question with no. Present and future well-being cannot be interdependent. The reason, in short, is that a theory of well-being that countenances both future-sensitivity and recursive dependence would have us understand a person's well-being at a time as so intricately tied to her well-being at other times that it would not make sense to consider her well-being an aspect of her state at particular times. It follows that we must reject either future-sensitivity or recursive dependence. I ultimately suggest, especially in light of arguments based on assumptions of empirical research on wellbeing, that the balance of reasons favors rejecting future-sensitivity.

Just as humans can draw conclusions responsibly or irresponsibly, so too can computers. Machine learning systems that have been trained on data sets that include irresponsible judgments are likely to yield irresponsible predictions as outputs. In this paper I focus on a particular kind of inference a computer system might make: identification of the intentions with which a person acted on the basis of photographic evidence. Such inferences are liable to be morally objectionable, because of a way in which they are presumptuous. After elaborating this moral concern, I explore the possibility that carefully procuring the training data for image recognition systems could ensure that the systems avoid the problem. The lesson of this paper extends beyond just the particular case of image recognition systems and the challenge of responsibly identifying a person's intentions. Reflection on this particular case demonstrates the importance (as well as the difficulty) of evaluating machine learning systems and their training data from the standpoint of moral considerations that are not encompassed by ordinary assessments of predictive accuracy.